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10 and counting: JQI's ultracold quantum gases

Data showing strontium BEC (inset) courtesy of Campbell group. The background image is a blue laser used in the lab. This experiment uses a total of 6 lasers in the process used to make a strontium quantum gas. (Laser photo credit/permissions: J. Consoli/UMD and JQI)

Gretchen Campbell’s UMD laboratory has reached an important milestone in their experiment: a strontium Bose-Einstein condensate (BEC). This brings the total number of ultracold quantum gases at JQI to 10. These experiments study a rich variety of topics, from quantum information to many-body physics. Campbell's lab is the third in the world to condense strontium into a quantum state.

Read more to learn more about these pristine quantum gases

Satyendra Bose and Albert Einstein predicted BECs about 85 years ago. Ultracold quantum gases, gases in their lowest possible energy state, can now be made of either fermionic or bosonic particles cooled to extremely low temperatures, roughly around 10-100 nK. Bosons trapped in a harmonic potential can ‘condense’ or occupy the same lowest energy ground state. Fermions, on the other hand, are not permitted to take on the same quantum state. Instead fermions do the next best thing by filling into the lowest set of energy levels, forming a state called a degenerate Fermi gas.

In 1995 BEC was achieved in dilute gases.  Physicists Eric Cornell, Carl Wieman, and Wolfgang Ketterle were later awarded the 2001 Nobel prize in physics for first creating these “atoms in unison,” which have been central to the explosion of experimental research in atomic systems. Degenerate Fermi gases were first achieved in 1999.

During the past 15-20 years scientists have dramatically improved upon the original experimental methods, increasing the number of atoms in these condensates from 1000 up to 107, with condensate lifetimes lasting minutes. Although considered part of the standard experimental toolbox for atomic physics, constructing BEC and degenerate Fermi gas experiments remains challenging. A clear recipe for making this ultracold quantum gas exists, yet the apparatus design remains highly dependent on the specific research objectives.

An orchestra of finely tuned devices must all perform harmoniously to produce this synchronized state of matter.  The players in this orchestration often include atomic beams, sophisticated electronics for stabilizing the laser frequencies, and vacuum systems having a pressure at around 10-14 atmospheres. This is at least a factor of 10 better than the vacuum in the region where satellites orbit the earth.

For young graduate students, postdoctoral researchers, and even advanced scientists, the initial observation of a quantum gas still exciting. In fact, it is the process of designing and building that students often learn much of the atomic physics foundation they will need to succeed. And although the road to new discoveries in this field is fraught with challenges, making a reliable quantum gas machine allows researchers to begin to study new physics.

While BEC occurs in superfluid helium, the widespread research in this field uses dilute ultracold gases because scientists can control this peculiar quantum system with amazing precision. Pristine, roughly identical BECs/Fermi Gases can be produced repeatedly in under a minute, making them an ideal and robust platform for experimentation.

A gas of ultracold atoms is more dilute than air, but these quantum systems can behave like crystals, giving physicists a novel way to simulate and understand materials. Atomic physicists have a somewhat unique set of knobs at their fingertips---for example, the ability to vary the strength of the atom-atom interactions. (In a condensed matter system, this would be like varying the electron-electron interactions, a parameter that is not controllable.) Even fluorescence from single atoms trapped in an optical lattice of light potentially can be resolved, reminiscent of the single atom control available in ion-trapping experiments.

For research reasons, physicists choose different atomic species when building a quantum gas. Often times, they pick alkali metals because of the characteristic internal structure (which resembles hydrogen) and the corresponding availability of lasers necessary to cool the atoms. At JQI there are two sodium BECs, five rubidium BECs, one potassium Fermi gas, one ytterbium BEC, and now the recently added strontium BEC in Campbell’s lab. While JQI labs are currently spread between the NIST and UMD campuses, most of these experiments are slated to move to the newly opened Physical Sciences Complex on UMD's campus.

JQI is a hub for ultracold quantum gas research, theoretical and experimental, which includes some of the following topics:

  • ultracold mixtures of gases 
  • BEC in disordered optical lattices
  • atomtronics with a toroidal BEC
  • light-induced vector potentials (making neutral atoms act as if they were charged particles)
  • BEC in double-well optical lattices and quantum information
  • spinor condensates
  • quantum simulation 

Recent Quantum Bits

October 17, 2016

Check out the second half of our feature story on Weyl semimetals and Weyl fermions, new materials and particles that have become a major focus for condensed matter researchers around the world. Part two looks at some of the theoretical work going on at JQI and CMTC. If you missed part one, it's not too late to catch up on the series. And if you missed our roundup of the research that led to last week's Nobel Prize in Physicsresearch that is closely related to Weyl materialswe encourage you to take a look.

JQI is also happy to congratulate Karina Jiménez-García on receiving a 2016 L'Oréal-UNESCO For Women in Science fellowship. "This is a recognition that I owe to all those that have guided and inspired me and those who have supported me throughout my professional career, especially my family," Jiménez-García said. We wrote a short story on how she plans to use the fellowship funds. It links to stories about the research she worked on while visiting JQI.

October 6, 2016

This year's Nobel Prize in Physics was awarded to three researchers who helped bring topology into physics. It's an innovation that has propelled condensed matter physics for the past three decades, leading recently to the discovery of several exotic materials.

We put together a roundup ( of the research that led to the prize and offered our take on topology. (Yes, we resorted to pastries.)

This year's prize is timely, too, as today we published part one ( of a two-part series on Weyl semimetals, topological materials with a long history. That history is due, in part, to this year's laureates: David Thouless, Duncan Haldane and Michael Kosterlitz.

Part one focuses on the history and basic physics of Weyl materials. Part two, which will appear next week, focuses on some of the research being explored by physicists at JQI and the Condensed Matter Theory Center at the University of Maryland.

September 15, 2016

From self-driving cars and IBM’s Watson to chess engines and AlphaGo, there is no shortage of news about machine learning, the field of artificial intelligence that studies how to make computers that can learn. Recently, parallel to these advances, scientists have started to ask how quantum devices and techniques might aid machine learning in the future.

To date, much research in the emerging field of quantum machine learning has attacked choke points in ordinary machine learning tasks, focusing, for example, on how to use quantum computers to speed up image recognition. But Vedran Dunjko and Hans Briegel at the University of Innsbruck, along with JQI Fellow Jake Taylor, have taken a broader view. Rather than focusing on speeding up subroutines for specific tasks, the researchers have introduced an approach to quantum machine learning that unifies much of the prior work and extends it to problems that received little attention before. They also showed how to increase learning performance for a large group of problems. The research has been accepted for publication in Physical Review Letters.

Quantum-enhanced machine learning. V. Dunjko, J. M. Taylor and H. J. Briegel, Physical Review Letters, to appear. arXiv:

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